This paper discusses the evaluation problem using observational data when the timing of treatment is an outcome of a stochastic process. We show that, without additional assumptions, it is not possible to estimate the average treatment effect and treatment on the treated. It is, however,...

This paper discusses the evaluation problem using observational data when the timing of treatment is an outcome of a stochastic process. We show that the duration framework in discrete time provides a fertile ground for effect evaluations. We suggest easy-to-use nonparametric survival function...

This paper investigates the method of matching regarding two crucial implementation choices, the distance measure and the type of algorithm. We implement optimal full matching - a fully efficient algorithm - and present a framework for statistical inference. The implementation uses data from the...

The evaluation of interventions such as active labor market policies or medical programs by means of a randomized controlled trial is often considered the gold standard. However, randomized experiments might face severe shortcomings especially if performed at the group level. One such problem is...

Propensity score matching is a prominent strategy to reduce imbalance in observational studies. However, if imbalance is considerable and the control reservoir is small, either one has to match one control to several treated units or, alternatively, discard many treated persons. The first...

The identification of average causal effects of a treatment in observational studies is typically based either on the unconfoundedness assumption or on the availability of an instrument. When available, instruments may also be used to test for the unconfoundedness assumption (exogeneity of the...

The identification of average causal effects of a treatment in observational studies is typically based either on the unconfoundedness assumption or on the availability of an instrument. When available, instruments may also be used to test for the unconfoundedness assumption (exogeneity of the...

This paper investigates the method of matching regarding two crucial implementation choices, the distance measure and the type of algorithm.We implement optimal full matching – a fully efficient algorithm – and present a framework for statistical inference. The implementation uses data from...